List of positional candidate genes after correcting for multiple testing and controlling the false discovery rate from genome wide association studies (GWAS) retrieved from the NHGRI-EBI Catalog of published genome-wide association studies (http://www.ebi.ac.uk/gwas/). The disease/trait examined in this study, as reported by the authors, was Exploratory eye movement dysfunction in schizophrenia (mean eye scanning length). The EFO term exploratory eye movement measurement was annotated to this set after curation by NHGRI-EBI. Intergenic SNPS were mapped to both the upstream and downstream gene. P-value uploaded. This gene set was generated using gwas2gs v. 0.1.8 and the GWAS Catalog v. 1.0.1.
Authors:
Y Ma, J Li, H Yu, L Wang, T Lu, C Pan, Y Han, D Zhang, W Yue
Postmortem tissue samples of the dorsolateral prefrontal cortex (DLPFC) from 153 deceased individuals (Mage = 35.4; 62% male; 77% European ancestry). Study groups included 72 brain samples from individuals who died of acute opioid intoxication, 53 psychiatric controls, and 28 normal controls. Whole transcriptome RNA-sequencing was used to generate exon counts, and differential expression was tested using limma-voom. Analyses were adjusted for relevant sociodemographic characteristics, technical covariates, and cryptic relatedness using quality surrogate variables. Weighted correlation network analysis and gene set enrichment analyses also were conducted.
Authors:
David W Sosnowski, Andrew E Jaffe, Ran Tao, Amy Deep-Soboslay, Chang Shu, Sarven Sabunciyan, Joel E Kleinman, Thomas M Hyde, Brion S Maher
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Mendez et al 2021_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Seney et al 2021_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Seney et al 2021_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Sosnowski et al 2022_log2FC
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Opioid_human_dorsolateral prefrontal cortex_reanalysis of Sosnowski et al 2022_qvalue
Description:
doi: https://doi.org/10.1101/2024.01.12.24301153. This study is a re-analysis of publicly available data and a meta-analysis investigating differential gene expression associated with opioid use disorder from Corradin et al. 2022 (PMID: 35301427); Mendez et al. 2021 (PMID: 34385598); Seney et al. 2021 (PMID: 34380600); and Sosnowski et al. 2022 (PMID:36845993 ). All four of these studies used human postmortem dorsolateral prefrontal cortex (DLPFC) brain tissue from donors identified as dying from OOD through toxicology assays administered by forensic scientists and phenotypic evidence of opioid addiction. Each of these independent studies had modest sample sizes (N = 40-153) and compared bulk RNA-seq data from individuals who died from OOD to individuals who died from non–drug use causes.
Study used cDNA microarrays to determine the gene expression profile in the hippocampus of DBA/2J (D2) and C57BL/6J (B6) mice during withdrawal after chronic and acute ethanol exposure and found strain- and treatment-specific patterns of altered expression. This gene set contains 31 ethanol withdrawal genes found to be upregulated in D2 mice during chronic ethanol treatment.
Striatum Gene Expression Correlates for VERCNT165 measured in BXD RI Females & Males obtained using GeneNetwork Striatum M430V2 (Apr05) RMA. The VERCNT165 measures Morphine vertical activity counts minutes 150-165 under the domain Morphine. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Striatum Gene Expression Correlates for VERCNT165 measured in BXD RI Females obtained using GeneNetwork Striatum M430V2 (Apr05) RMA. The VERCNT165 measures Morphine vertical activity counts minutes 150-165 under the domain Morphine. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Striatum Gene Expression Correlates for VERCNT180 measured in BXD RI Females obtained using GeneNetwork Striatum M430V2 (Apr05) RMA. The VERCNT180 measures Morphine vertical activity counts minutes 165-180 under the domain Morphine. The correlates were thresholded at a p-value of less than 0.001.
Authors:
Philip VM, Duvvuru S, Gomero B, Ansah TA, Blaha CD, Cook MN, Hamre KM, Lariviere WR, Matthews DB, Mittleman G, Goldowitz D, Chesler EJ
Differentially expressed in the Nucleus accumbens following 24 hr continuous 9.5g/kg/day alcohol drinking vs. water drinking in alcohol preferring rats. Estimated BAC in the alcohol exposed group was > 85mg%. The 406 significanlty different probe sets represent 374 uniquely named genes, with most gene expression differences in the range of 1.1-1.3 fold.
Genes with a mean fold change > 1.5 or < 0.7 were selected and annotated. Values are taken from microarray analysis and represent mean ratios of alcoholic cases compared with matched control cases(n = 6). P values were from t-test; from Flatscher-Bader et al., 2005
Authors:
Flatscher-Bader T, van der Brug M, Hwang JW, Gochee PA, Matsumoto I, Niwa S, Wilce PA
QTL for differences in cocaine responsiveness on Chr17 at Ck-2 (45.25 Mbp , Build 37)
Description:
differences in cocaine responsiveness spans 20.25 - 70.25 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for differences in cocaine responsiveness on Chr17 at D17MIt7 (51.99 Mbp , Build 37)
Description:
differences in cocaine responsiveness spans 26.99 - 76.99 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for t-psl on Chr17 at Hp (53.97 Mbp , Build 37)
Description:
t-psl spans 28.97 - 78.97 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for differences in cocaine responsiveness on Chr17 at DI7Mft3 (64.20 Mbp , Build 37)
Description:
differences in cocaine responsiveness spans 39.20 - 89.20 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for METH responses for home cage activity on Chr17 at D17Mit3 (70.84 Mbp , Build 37)
Description:
METH responses for home cage activity spans 45.84 - 95.84 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for METH responses for chewing on Chr17 at Hprt-ps1 (77.06 Mbp , Build 37)
Description:
METH responses for chewing spans 52.06 - 102.06 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for nicotine sensitivity on Chr17 at D17Mit76 (84.11 Mbp , Build 37)
Description:
nicotine sensitivity spans 59.11 - 109.11 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
QTL for nicotine sensitivity on Chr17 at D17Mit221 (86.51 Mbp , Build 37)
Description:
nicotine sensitivity spans 61.51 - 111.51 Mbp (NCBI Build 37) on Chr17. This interval was obtained by using an interval width of 25 Mbp around the peak marker (Build 37, MGI, http://informatics.jax.org).
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